Overview

Dataset statistics

Number of variables23
Number of observations729308
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory93.9 MiB
Average record size in memory135.0 B

Variable types

NUM15
CAT7
BOOL1

Warnings

dropoff_datetime_hour is highly correlated with pickup_datetime_hourHigh correlation
pickup_datetime_hour is highly correlated with dropoff_datetime_hourHigh correlation
dropoff_datetime_woy is highly correlated with pickup_datetime_woyHigh correlation
pickup_datetime_woy is highly correlated with dropoff_datetime_woyHigh correlation
dropoff_datetime_doy is highly correlated with pickup_datetime_doyHigh correlation
pickup_datetime_doy is highly correlated with dropoff_datetime_doyHigh correlation
dropoff_datetime_moy is highly correlated with pickup_datetime_moyHigh correlation
pickup_datetime_moy is highly correlated with dropoff_datetime_moyHigh correlation
dropoff_datetime_dow is highly correlated with pickup_datetime_dowHigh correlation
pickup_datetime_dow is highly correlated with dropoff_datetime_dowHigh correlation
pickup_longitude is highly skewed (γ1 = -444.2406389) Skewed
pickup_latitude is highly skewed (γ1 = 35.3716491) Skewed
dropoff_longitude is highly skewed (γ1 = -449.9053254) Skewed
dropoff_latitude is highly skewed (γ1 = -23.50426371) Skewed
trip_duration is highly skewed (γ1 = 25.58353865) Skewed
distance is highly skewed (γ1 = 40.98349517) Skewed
speed is highly skewed (γ1 = 194.6545591) Skewed
df_index has unique values Unique
id has unique values Unique
pickup_datetime_hour has 26722 (3.7%) zeros Zeros
dropoff_datetime_hour has 28910 (4.0%) zeros Zeros

Reproduction

Analysis started2020-12-24 16:25:47.298799
Analysis finished2020-12-24 16:27:42.250453
Duration1 minute and 54.95 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIQUE

Distinct729308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean364661.1247
Minimum0
Maximum729321
Zeros1
Zeros (%)< 0.1%
Memory size5.6 MiB
2020-12-24T11:27:42.594252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36466.35
Q1182331.75
median364661.5
Q3546991.25
95-th percentile692855.65
Maximum729321
Range729321
Interquartile range (IQR)364659.5

Descriptive statistics

Standard deviation210537.1167
Coefficient of variation (CV)0.5773500448
Kurtosis-1.199995945
Mean364661.1247
Median Absolute Deviation (MAD)182330
Skewness-6.839068838e-07
Sum2.659502755e+11
Variance4.432587749e+10
MonotocityStrictly increasing
2020-12-24T11:27:42.711114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
5380281< 0.1%
 
7264721< 0.1%
 
5687671< 0.1%
 
5667181< 0.1%
 
5728611< 0.1%
 
5708121< 0.1%
 
5605711< 0.1%
 
5585221< 0.1%
 
5646651< 0.1%
 
Other values (729298)729298> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
ValueCountFrequency (%) 
7293211< 0.1%
 
7293201< 0.1%
 
7293191< 0.1%
 
7293181< 0.1%
 
7293171< 0.1%
 

id
Categorical

UNIQUE

Distinct729308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.6 MiB
id0764556
 
1
id2007948
 
1
id3832513
 
1
id0660360
 
1
id3379066
 
1
Other values (729303)
729303 
ValueCountFrequency (%) 
id07645561< 0.1%
 
id20079481< 0.1%
 
id38325131< 0.1%
 
id06603601< 0.1%
 
id33790661< 0.1%
 
id36901751< 0.1%
 
id24463681< 0.1%
 
id34614641< 0.1%
 
id30982791< 0.1%
 
id14251461< 0.1%
 
Other values (729298)729298> 99.9%
 
2020-12-24T11:27:45.777874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique729308 ?
Unique (%)100.0%
2020-12-24T11:27:45.896477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length9
Mean length9
Min length9

vendor_id
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.3 KiB
2
390477 
1
338831 
ValueCountFrequency (%) 
239047753.5%
 
133883146.5%
 
2020-12-24T11:27:45.999176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-24T11:27:46.065953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:46.140662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

passenger_count
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.6 KiB
1
517403 
2
105096 
5
 
38926
3
 
29692
6
 
24107
Other values (4)
 
14084
ValueCountFrequency (%) 
151740370.9%
 
210509614.4%
 
5389265.3%
 
3296924.1%
 
6241073.3%
 
4140501.9%
 
032< 0.1%
 
91< 0.1%
 
71< 0.1%
 
2020-12-24T11:27:46.247499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-12-24T11:27:46.324244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:46.462893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

pickup_longitude
Real number (ℝ)

SKEWED

Distinct19727
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-73.97351416
Minimum-121.933342
Maximum-65.89738464
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:46.574808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-121.933342
5-th percentile-74.00688171
Q1-73.99185944
median-73.98175812
Q3-73.96736145
95-th percentile-73.89160156
Maximum-65.89738464
Range56.03595734
Interquartile range (IQR)0.02449798584

Descriptive statistics

Standard deviation0.06975319339
Coefficient of variation (CV)-0.0009429482184
Kurtosis306798.7741
Mean-73.97351416
Median Absolute Deviation (MAD)0.01175689697
Skewness-444.2406389
Sum-53949475.67
Variance0.004865507988
MonotocityNot monotonic
2020-12-24T11:27:46.685965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-73.98213959317< 0.1%
 
-73.98220062316< 0.1%
 
-73.98210144308< 0.1%
 
-73.98226166297< 0.1%
 
-73.98209381296< 0.1%
 
-73.98220825288< 0.1%
 
-73.98223877286< 0.1%
 
-73.9822464285< 0.1%
 
-73.9821167284< 0.1%
 
-73.98238373283< 0.1%
 
Other values (19717)72634899.6%
 
ValueCountFrequency (%) 
-121.9333421< 0.1%
 
-79.569732671< 0.1%
 
-78.547401431< 0.1%
 
-77.896018981< 0.1%
 
-77.039436341< 0.1%
 
ValueCountFrequency (%) 
-65.897384641< 0.1%
 
-70.511901861< 0.1%
 
-71.88164521< 0.1%
 
-72.074333191< 0.1%
 
-72.42122651< 0.1%
 

pickup_latitude
Real number (ℝ≥0)

SKEWED

Distinct39775
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.7509192
Minimum34.7122345
Maximum51.88108444
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:46.825313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum34.7122345
5-th percentile40.70815659
Q140.73733521
median40.75407028
Q340.76831436
95-th percentile40.78828049
Maximum51.88108444
Range17.16884995
Interquartile range (IQR)0.03097915649

Descriptive statistics

Standard deviation0.03359367798
Coefficient of variation (CV)0.0008243661405
Kurtosis19349.80421
Mean40.7509192
Median Absolute Deviation (MAD)0.01529312134
Skewness35.3716491
Sum29719971.38
Variance0.0011285352
MonotocityNot monotonic
2020-12-24T11:27:46.943145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
40.77410126202< 0.1%
 
40.77407837201< 0.1%
 
40.77412033197< 0.1%
 
40.77408981196< 0.1%
 
40.77405167196< 0.1%
 
40.77410889194< 0.1%
 
40.77415848182< 0.1%
 
40.7741394181< 0.1%
 
40.77407074171< 0.1%
 
40.77413177167< 0.1%
 
Other values (39765)72742199.7%
 
ValueCountFrequency (%) 
34.71223451< 0.1%
 
35.310306551< 0.1%
 
37.389381411< 0.1%
 
37.7777711< 0.1%
 
38.898849491< 0.1%
 
ValueCountFrequency (%) 
51.881084441< 0.1%
 
43.911762241< 0.1%
 
43.486885071< 0.1%
 
43.139652251< 0.1%
 
42.458942411< 0.1%
 

dropoff_longitude
Real number (ℝ)

SKEWED

Distinct27891
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-73.97342304
Minimum-121.9333038
Maximum-65.89738464
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:47.080540image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-121.9333038
5-th percentile-74.00753021
Q1-73.99131775
median-73.97975922
Q3-73.96303558
95-th percentile-73.92024994
Maximum-65.89738464
Range56.03591919
Interquartile range (IQR)0.02828216553

Descriptive statistics

Standard deviation0.0695878374
Coefficient of variation (CV)-0.0009407140366
Kurtosis309935.976
Mean-73.97342304
Median Absolute Deviation (MAD)0.01315307617
Skewness-449.9053254
Sum-53949409.21
Variance0.004842467114
MonotocityNot monotonic
2020-12-24T11:27:47.197332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-73.98233032239< 0.1%
 
-73.98209381224< 0.1%
 
-73.99140167222< 0.1%
 
-73.9821167220< 0.1%
 
-73.9822464217< 0.1%
 
-73.98220062212< 0.1%
 
-73.98222351212< 0.1%
 
-73.98235321208< 0.1%
 
-73.99134064206< 0.1%
 
-73.99137878205< 0.1%
 
Other values (27881)72714399.7%
 
ValueCountFrequency (%) 
-121.93330381< 0.1%
 
-80.35543061< 0.1%
 
-79.817977911< 0.1%
 
-79.786132811< 0.1%
 
-79.518615721< 0.1%
 
ValueCountFrequency (%) 
-65.897384641< 0.1%
 
-70.511901861< 0.1%
 
-71.88164521< 0.1%
 
-72.022407531< 0.1%
 
-72.42122651< 0.1%
 

dropoff_latitude
Real number (ℝ≥0)

SKEWED

Distinct53578
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.75177559
Minimum32.1811409
Maximum43.92102814
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:47.335206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum32.1811409
5-th percentile40.69980621
Q140.7359314
median40.75450897
Q340.76974106
95-th percentile40.79736328
Maximum43.92102814
Range11.73988724
Interquartile range (IQR)0.03380966187

Descriptive statistics

Standard deviation0.03603704846
Coefficient of variation (CV)0.0008843062159
Kurtosis5639.454966
Mean40.75177559
Median Absolute Deviation (MAD)0.01668930054
Skewness-23.50426371
Sum29720595.95
Variance0.001298668862
MonotocityNot monotonic
2020-12-24T11:27:47.462337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
40.75014877145< 0.1%
 
40.75017166137< 0.1%
 
40.75003815136< 0.1%
 
40.75014114132< 0.1%
 
40.77433014126< 0.1%
 
40.75009155126< 0.1%
 
40.75019836125< 0.1%
 
40.75011826124< 0.1%
 
40.75598145123< 0.1%
 
40.77431107122< 0.1%
 
Other values (53568)72801299.8%
 
ValueCountFrequency (%) 
32.18114091< 0.1%
 
35.173545841< 0.1%
 
37.389511111< 0.1%
 
37.7777711< 0.1%
 
38.478298191< 0.1%
 
ValueCountFrequency (%) 
43.921028141< 0.1%
 
43.911762241< 0.1%
 
43.486885071< 0.1%
 
43.139652251< 0.1%
 
42.458942411< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.3 KiB
N
725268 
Y
 
4040
ValueCountFrequency (%) 
N72526899.4%
 
Y40400.6%
 
2020-12-24T11:27:47.554033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

trip_duration
Real number (ℝ≥0)

SKEWED

Distinct6294
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean949.5877009
Minimum2
Maximum86391
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:47.885925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile180
Q1397
median663
Q31075
95-th percentile2102
Maximum86391
Range86389
Interquartile range (IQR)678

Descriptive statistics

Standard deviation3127.54733
Coefficient of variation (CV)3.293584497
Kurtosis684.7457004
Mean949.5877009
Median Absolute Deviation (MAD)311
Skewness25.58353865
Sum692541907
Variance9781552.304
MonotocityNot monotonic
2020-12-24T11:27:48.001734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
3488300.1%
 
3688080.1%
 
3638080.1%
 
3888050.1%
 
3587980.1%
 
4047930.1%
 
3377910.1%
 
3767880.1%
 
3077870.1%
 
3547870.1%
 
Other values (6284)72131398.9%
 
ValueCountFrequency (%) 
2102< 0.1%
 
3163< 0.1%
 
4139< 0.1%
 
5136< 0.1%
 
695< 0.1%
 
ValueCountFrequency (%) 
863911< 0.1%
 
863871< 0.1%
 
863781< 0.1%
 
863771< 0.1%
 
863692< 0.1%
 

pickup_datetime_moy
Categorical

HIGH CORRELATION

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.4 KiB
3
128314 
4
125630 
5
124200 
2
119361 
6
117406 
ValueCountFrequency (%) 
312831417.6%
 
412563017.2%
 
512420017.0%
 
211936116.4%
 
611740616.1%
 
111439715.7%
 
2020-12-24T11:27:48.127362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-24T11:27:48.212077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:48.327645image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

pickup_datetime_hour
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.61177308
Minimum0
Maximum23
Zeros26722
Zeros (%)3.7%
Memory size5.6 MiB
2020-12-24T11:27:48.419826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median14
Q319
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.402809936
Coefficient of variation (CV)0.4703876489
Kurtosis-0.7222696722
Mean13.61177308
Median Absolute Deviation (MAD)5
Skewness-0.4455755069
Sum9927175
Variance40.99597507
MonotocityNot monotonic
2020-12-24T11:27:48.515015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
18454046.2%
 
19452616.2%
 
20421655.8%
 
21420455.8%
 
22402935.5%
 
17383135.3%
 
14371205.1%
 
12358184.9%
 
15356874.9%
 
13356294.9%
 
Other values (14)33157345.5%
 
ValueCountFrequency (%) 
0267223.7%
 
1192432.6%
 
2139601.9%
 
3104241.4%
 
478271.1%
 
ValueCountFrequency (%) 
23350684.8%
 
22402935.5%
 
21420455.8%
 
20421655.8%
 
19452616.2%
 

pickup_datetime_woy
Real number (ℝ≥0)

HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.84390134
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:48.609979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median13
Q320
95-th percentile25
Maximum53
Range52
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.558288252
Coefficient of variation (CV)0.6181991652
Kurtosis3.948221195
Mean13.84390134
Median Absolute Deviation (MAD)6
Skewness1.178425445
Sum10096468
Variance73.24429781
MonotocityNot monotonic
2020-12-24T11:27:48.715557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%) 
14304114.2%
 
15300794.1%
 
9300594.1%
 
18297924.1%
 
11295634.1%
 
6294804.0%
 
8293614.0%
 
20293254.0%
 
10288784.0%
 
19288294.0%
 
Other values (17)43353159.4%
 
ValueCountFrequency (%) 
1264743.6%
 
2282863.9%
 
3226813.1%
 
4269833.7%
 
5281103.9%
 
ValueCountFrequency (%) 
5399731.4%
 
26149492.0%
 
25270843.7%
 
24271433.7%
 
23277983.8%
 

pickup_datetime_dow
Categorical

HIGH CORRELATION

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.6 KiB
4
111744 
5
110249 
3
109344 
2
105071 
1
101252 
Other values (2)
191648 
ValueCountFrequency (%) 
411174415.3%
 
511024915.1%
 
310934415.0%
 
210507114.4%
 
110125213.9%
 
69767913.4%
 
09396912.9%
 
2020-12-24T11:27:48.830644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-24T11:27:48.913370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:49.036757image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

pickup_datetime_doy
Real number (ℝ≥0)

HIGH CORRELATION

Distinct182
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.88311386
Minimum1
Maximum182
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:49.142774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q148
median92
Q3136
95-th percentile173
Maximum182
Range181
Interquartile range (IQR)88

Descriptive statistics

Standard deviation51.55562169
Coefficient of variation (CV)0.5611000708
Kurtosis-1.159208695
Mean91.88311386
Median Absolute Deviation (MAD)44
Skewness-0.001481419285
Sum67011090
Variance2657.982128
MonotocityNot monotonic
2020-12-24T11:27:49.262425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10049000.7%
 
10748460.7%
 
6547840.7%
 
7246820.6%
 
6446730.6%
 
5846690.6%
 
10646580.6%
 
12846510.6%
 
9946380.6%
 
9346340.6%
 
Other values (172)68217393.5%
 
ValueCountFrequency (%) 
135880.5%
 
232280.4%
 
331570.4%
 
433410.5%
 
535940.5%
 
ValueCountFrequency (%) 
18238770.5%
 
18138380.5%
 
18036320.5%
 
17936020.5%
 
17835900.5%
 

dropoff_datetime_moy
Categorical

HIGH CORRELATION

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.6 KiB
3
128282 
4
125629 
5
124235 
2
119358 
6
117380 
Other values (2)
114424 
ValueCountFrequency (%) 
312828217.6%
 
412562917.2%
 
512423517.0%
 
211935816.4%
 
611738016.1%
 
111437115.7%
 
753< 0.1%
 
2020-12-24T11:27:49.392975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-24T11:27:49.470683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:49.594421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

dropoff_datetime_hour
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.60621987
Minimum0
Maximum23
Zeros28910
Zeros (%)4.0%
Memory size5.6 MiB
2020-12-24T11:27:49.686894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median14
Q319
95-th percentile23
Maximum23
Range23
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.486347395
Coefficient of variation (CV)0.4767192841
Kurtosis-0.7263072763
Mean13.60621987
Median Absolute Deviation (MAD)5
Skewness-0.4637741247
Sum9923125
Variance42.07270253
MonotocityNot monotonic
2020-12-24T11:27:49.781390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%) 
19468526.4%
 
18448626.2%
 
20427895.9%
 
21418485.7%
 
22407245.6%
 
23365995.0%
 
15364465.0%
 
14361245.0%
 
17360144.9%
 
12357164.9%
 
Other values (14)33133445.4%
 
ValueCountFrequency (%) 
0289104.0%
 
1208852.9%
 
2148872.0%
 
3110131.5%
 
484741.2%
 
ValueCountFrequency (%) 
23365995.0%
 
22407245.6%
 
21418485.7%
 
20427895.9%
 
19468526.4%
 

dropoff_datetime_woy
Real number (ℝ≥0)

HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.84297718
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:49.876529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median13
Q320
95-th percentile25
Maximum53
Range52
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.555330412
Coefficient of variation (CV)0.6180267656
Kurtosis3.942279069
Mean13.84297718
Median Absolute Deviation (MAD)6
Skewness1.176534395
Sum10095794
Variance73.19367847
MonotocityNot monotonic
2020-12-24T11:27:49.983296image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%) 
14304094.2%
 
15300804.1%
 
9300484.1%
 
18297954.1%
 
11295644.1%
 
6294714.0%
 
8293654.0%
 
20293214.0%
 
10288824.0%
 
19288314.0%
 
Other values (17)43354259.4%
 
ValueCountFrequency (%) 
1264883.6%
 
2282683.9%
 
3226883.1%
 
4269813.7%
 
5281023.9%
 
ValueCountFrequency (%) 
5399461.4%
 
26149782.1%
 
25270863.7%
 
24271413.7%
 
23277923.8%
 

dropoff_datetime_dow
Categorical

HIGH CORRELATION

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size712.6 KiB
4
111509 
5
110286 
3
108918 
2
104940 
1
101141 
Other values (2)
192514 
ValueCountFrequency (%) 
411150915.3%
 
511028615.1%
 
310891814.9%
 
210494014.4%
 
110114113.9%
 
69855813.5%
 
09395612.9%
 
2020-12-24T11:27:50.102899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-24T11:27:50.182633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:50.302963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

dropoff_datetime_doy
Real number (ℝ≥0)

HIGH CORRELATION

Distinct183
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.89431214
Minimum1
Maximum183
Zeros0
Zeros (%)0.0%
Memory size5.6 MiB
2020-12-24T11:27:50.411835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q148
median92
Q3136
95-th percentile173
Maximum183
Range182
Interquartile range (IQR)88

Descriptive statistics

Standard deviation51.55641851
Coefficient of variation (CV)0.5610403659
Kurtosis-1.159205774
Mean91.89431214
Median Absolute Deviation (MAD)44
Skewness-0.001492861615
Sum67019257
Variance2658.064289
MonotocityNot monotonic
2020-12-24T11:27:50.532434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10049030.7%
 
10748530.7%
 
6548020.7%
 
7246920.6%
 
5846610.6%
 
12846570.6%
 
10646460.6%
 
6446290.6%
 
9346210.6%
 
4446110.6%
 
Other values (173)68223393.5%
 
ValueCountFrequency (%) 
135520.5%
 
232210.4%
 
331730.4%
 
433440.5%
 
535950.5%
 
ValueCountFrequency (%) 
18353< 0.1%
 
18238640.5%
 
18138300.5%
 
18036370.5%
 
17935940.5%
 

distance
Real number (ℝ≥0)

SKEWED

Distinct726232
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.138251114
Minimum0
Maximum771.0659931
Zeros2897
Zeros (%)0.4%
Memory size5.6 MiB
2020-12-24T11:27:50.935135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3703227188
Q10.7659758823
median1.302249156
Q32.408757991
95-th percentile6.830951969
Maximum771.0659931
Range771.0659931
Interquartile range (IQR)1.642782109

Descriptive statistics

Standard deviation2.704898481
Coefficient of variation (CV)1.265005061
Kurtosis9795.507455
Mean2.138251114
Median Absolute Deviation (MAD)0.6611833846
Skewness40.98349517
Sum1559443.643
Variance7.316475794
MonotocityNot monotonic
2020-12-24T11:27:51.059806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
028970.4%
 
0.000263570487421< 0.1%
 
0.000263570487220< 0.1%
 
0.000263570486918< 0.1%
 
0.00079071146113< 0.1%
 
0.000263570486712< 0.1%
 
0.000527140973910< 0.1%
 
0.00026357048768< 0.1%
 
0.00026357048658< 0.1%
 
0.00052714097418< 0.1%
 
Other values (726222)72629399.6%
 
ValueCountFrequency (%) 
028970.4%
 
0.00026357048581< 0.1%
 
0.00026357048581< 0.1%
 
0.00026357048611< 0.1%
 
0.00026357048614< 0.1%
 
ValueCountFrequency (%) 
771.06599311< 0.1%
 
357.21154371< 0.1%
 
339.17811851< 0.1%
 
198.91721541< 0.1%
 
195.58568451< 0.1%
 

speed
Real number (ℝ≥0)

SKEWED

Distinct726394
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.960500414
Minimum0
Maximum3504.845423
Zeros2897
Zeros (%)0.4%
Memory size5.6 MiB
2020-12-24T11:27:51.474424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.132438836
Q15.669613674
median7.951610556
Q311.08760375
95-th percentile18.31075623
Maximum3504.845423
Range3504.845423
Interquartile range (IQR)5.41799008

Descriptive statistics

Standard deviation7.658905795
Coefficient of variation (CV)0.8547408562
Kurtosis77253.68241
Mean8.960500414
Median Absolute Deviation (MAD)2.597411864
Skewness194.6545591
Sum6534964.636
Variance58.65883798
MonotocityNot monotonic
2020-12-24T11:27:51.593028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
028970.4%
 
0.31628458494< 0.1%
 
0.18977075063< 0.1%
 
0.094885375612< 0.1%
 
0.072988750412< 0.1%
 
0.094885375462< 0.1%
 
0.039535573072< 0.1%
 
0.091824556772< 0.1%
 
0.10542819492< 0.1%
 
0.35582015762< 0.1%
 
Other values (726384)72639099.6%
 
ValueCountFrequency (%) 
028970.4%
 
1.665061704e-051< 0.1%
 
2.933512205e-051< 0.1%
 
3.437170215e-051< 0.1%
 
0.00048680342221< 0.1%
 
ValueCountFrequency (%) 
3504.8454231< 0.1%
 
2539.3687081< 0.1%
 
876.14999351< 0.1%
 
874.9570181< 0.1%
 
839.93444981< 0.1%
 

trip_duration_minutes
Real number (ℝ)

Distinct6294
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.370417623
Minimum-3.401197382
Maximum7.27229422
Zeros91
Zeros (%)< 0.1%
Memory size5.6 MiB
2020-12-24T11:27:51.728499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-3.401197382
5-th percentile1.098612289
Q11.889591718
median2.402430428
Q32.885731378
95-th percentile3.556299989
Maximum7.27229422
Range10.6734916
Interquartile range (IQR)0.9961396599

Descriptive statistics

Standard deviation0.7980667351
Coefficient of variation (CV)0.3366776923
Kurtosis4.049775234
Mean2.370417623
Median Absolute Deviation (MAD)0.4978384282
Skewness-0.3437861951
Sum1728764.536
Variance0.6369105137
MonotocityNot monotonic
2020-12-24T11:27:51.847400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.7578579188300.1%
 
1.8137383768080.1%
 
1.8000582728080.1%
 
1.8666607778050.1%
 
1.7861884247980.1%
 
1.9070703167930.1%
 
1.7257383687910.1%
 
1.8352445817880.1%
 
1.7749523517870.1%
 
1.6325031857870.1%
 
Other values (6284)72131398.9%
 
ValueCountFrequency (%) 
-3.401197382102< 0.1%
 
-2.995732274163< 0.1%
 
-2.708050201139< 0.1%
 
-2.48490665136< 0.1%
 
-2.30258509395< 0.1%
 
ValueCountFrequency (%) 
7.272294221< 0.1%
 
7.2722479181< 0.1%
 
7.2721437311< 0.1%
 
7.2721321531< 0.1%
 
7.2720395322< 0.1%
 

Interactions

2020-12-24T11:26:33.151584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:33.458611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:33.746644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:34.034633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:34.322672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:34.609761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:34.911755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:35.209759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:35.512746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:35.819569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:36.118540image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:36.421793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:36.784618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:37.067021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:37.366137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:37.636865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:37.914443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:38.183157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:38.458639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:38.732152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:39.014851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:39.296360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:39.578824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:39.864001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:40.153967image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:40.441398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:40.731511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:41.004061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:41.285106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:41.576984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:41.839975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:42.127974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:42.406779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:42.689200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:42.970819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:43.252186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:43.548394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:43.843771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:44.139687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:44.440032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:44.731182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:45.024752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:45.301087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:45.582571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:45.980925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:46.253787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:46.531274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:46.799791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:47.078106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:47.347376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:47.617818image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:47.899307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:48.182514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:48.469336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:48.762706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:49.048031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:49.333263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:49.602858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:49.874881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:50.166304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:50.431045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:50.707698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:50.980117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:51.258861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:51.531756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:51.802395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:52.086657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:52.377038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:52.666612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:52.959651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:53.250952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:53.551049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:53.826656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:54.105163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:54.398629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:54.667494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:54.935602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:55.196728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:55.464832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:55.727957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:55.986505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:56.256125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:56.530047image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:56.803377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:57.207353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:57.485386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:57.765006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:58.028656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:58.292473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:58.577961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:58.848738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:59.128806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:59.405877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:59.682949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:26:59.959026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:00.228128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:00.513175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:00.799222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:01.088256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:01.388252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:01.673301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:01.962336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:02.231439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:02.505522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:02.804523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:03.074620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:03.355681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:03.635746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:03.917804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:04.199863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:04.474945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:04.763979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:05.054010image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:05.346033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:05.643043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:05.934069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:06.229085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:06.506194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:06.784231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:07.085224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:07.356319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:07.644356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:07.934389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:08.224420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:08.507474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:08.788536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:09.085544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:09.382551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:09.682549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:09.990520image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:10.286531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:10.587528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:10.871577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:11.312106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:11.620077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:11.904129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:12.189178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:12.465256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:12.739339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:13.013479image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:13.287510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:13.570564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:13.855610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:14.148632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:14.441653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:14.728694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:15.020738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:15.292813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:15.569887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:15.865159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:16.133122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:16.411466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:16.689315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:16.968925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:17.242395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:17.514084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:17.800377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:18.089955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:18.380979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:18.678151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:18.965810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:19.256837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:19.531919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:19.810987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:20.111983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:20.389056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:20.679088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:20.968122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:21.260177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:21.547188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:21.830249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:22.130240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:22.427248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:22.730236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:23.080068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:23.380066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:23.681061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:23.999995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:24.292020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:24.602981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:24.874075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:25.163110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:25.443174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:25.728223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:26.007291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:26.282374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:26.569413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:26.857451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:27.151468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:27.449482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:27.738508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:28.031530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:28.496975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:28.812923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:29.158768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:29.435839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:29.746801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:30.046798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:30.326864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:30.598955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:30.871045image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:31.156095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:31.454098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:31.740142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:32.032167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:32.320204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:32.606251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:32.880335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:33.159402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:33.453419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:33.732488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:34.014545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:34.295606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:34.573678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:34.846766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:35.116865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:35.404951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:35.689953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:35.981397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:36.273807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:36.556055image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:36.847499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:37.117381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:37.390972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:37.682175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-12-24T11:27:51.969993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-24T11:27:52.207759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-24T11:27:52.444013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-24T11:27:52.691350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-24T11:27:52.963480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-24T11:27:38.798389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-24T11:27:39.967423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

df_indexidvendor_idpassenger_countpickup_longitudepickup_latitudedropoff_longitudedropoff_latitudestore_and_fwd_flagtrip_durationpickup_datetime_moypickup_datetime_hourpickup_datetime_woypickup_datetime_dowpickup_datetime_doydropoff_datetime_moydropoff_datetime_hourdropoff_datetime_woydropoff_datetime_dowdropoff_datetime_doydistancespeedtrip_duration_minutes
00id108078421-73.95391840.778873-73.96387540.771164N400216906021690600.7450706.7056321.897120
11id088988512-73.98831240.731743-73.99475140.694931N110032310471323104712.5657148.3968832.908721
22id085791222-73.99731440.721458-73.94802940.774918N1635217765221876524.5054159.9201813.305054
33id374427326-73.96167040.759720-73.95677940.780628N1141191151101151.4671204.6289502.945316
44id023293911-74.01712040.708469-73.98818240.740631N8482672482672482.68963011.4182412.648536
55id191806922-73.99361440.751884-73.99542240.723862N1455218664521866451.9385014.7962923.188417
66id242902811-73.96508040.758915-73.97680740.764107N3974201621114201621110.7108376.4458731.889592
77id166379821-73.96389040.765434-73.87242940.774200N11016162461716172461714.82407715.7735502.909630
88id243694322-73.87288740.774281-73.97901940.761879N188631913088319130885.61947010.7264533.447869
99id293390911-73.98782340.740982-73.99915340.686451N14294221461014221461013.8141759.6088373.170386

Last rows

df_indexidvendor_idpassenger_countpickup_longitudepickup_latitudedropoff_longitudedropoff_latitudestore_and_fwd_flagtrip_durationpickup_datetime_moypickup_datetime_hourpickup_datetime_woypickup_datetime_dowpickup_datetime_doydropoff_datetime_moydropoff_datetime_hourdropoff_datetime_woydropoff_datetime_dowdropoff_datetime_doydistancespeedtrip_duration_minutes
729298729312id368313721-73.98477940.779781-73.99871840.739777N15261053411153412.8587086.7440023.236061
729299729313id399390711-73.99403440.751015-74.00373840.722240N1325211543621154362.0520045.5752573.094823
729300729314id322612922-73.98774040.748222-73.94958540.680737N1338331208134120815.07293613.6491553.104587
729301729315id323403211-73.98411640.725372-73.98254440.731377N11066261180662611800.42294313.8417670.606136
729302729316id203109021-73.97448740.783138-73.95262940.772270N449122402512240251.36813310.9694392.012678
729303729317id390598222-73.96591940.789780-73.95263740.789181N2965132051425132051420.6960758.4657801.596015
729304729318id010286111-73.99666640.737434-74.00132040.731911N3152080532080530.4527975.1748201.658228
729305729319id043969911-73.99784940.761696-74.00148840.741207N6734181541064191541061.4283957.6407452.417401
729306729320id207891211-74.00670640.708244-74.01355040.713814N44769246171692461710.5258774.2352512.008214
729307729321id105344124-74.00334240.743839-73.94584740.712841N1224117534111753413.69457710.8664043.015535